Blog by James Millington, PhD

Tag: Political

It can be hard not to abandon hope for a sustainable future when you read about our rapidly growing global population and the hopes of those in the developing world (growing the fastest) to lead more ‘western’ lifestyles. For ‘western’, read ‘consumptive’. Last year Jared Diamond came up with new numbers to make us feel even more hopeless; economically more developed countries are consuming resources and producing waste 32 times faster than less developed countries. That means, Diamond estimates, if everyone on earth were to eat as much meat, drive their cars as far and use electricity as prodigiously as Europeans, Americans and Japanese currently do it would be as if the human population had suddenly ballooned to 72 billion.

In an editorial in the latest issue of Conservation Biology, R. Edward Grumbine and Jianchu Xu use Diamond’s example when discussing the rise of China as a global economic power and consumer and the potential implications for conservation, the environment and the climate debate:

“China’s rapid economic rise has not helped conservation much. The country faces severe environmental challenges as the largest human population in history builds highways, factories, and housing to fully join the modern industrial world. The PRC [People’s Republic of China], however, remains relatively poor. Per capita income in 2007 was a mere one-fifth of the U.S. average; a typical American teenager has more discretionary income than the total annual salary of the average Chinese citizen.

Despite the importance of biodiversity issues, we want to draw attention to less-discussed environmental concerns that involve China at regional and global scales and which will likely transform life for all of us over the rest of the 21st century.”

Focusing on their discussion about issues related to climate change, Grumbine and Xu point out;

“Even if the European Union and the United States magically reduced their greenhouse gas emissions to zero while you are reading this sentence, China’s current pace by itself may keep global emissions rising through 2020.

China should not be blamed for the world’s runaway greenhouse gas emissions; the United States never even ratified the Kyoto Protocol. And we emphasize that China’s development dream is not a vision exclusive to the PRC. Beyond the Middle Kingdom, there are at least 1.2 billion people desiring cars, a decent house attached to a sewer system, potable water, and a fair measure of education and health care.”

The consequences of Chinese, and other poorer nations, realising their hopes of economic development?

“China and the rest of the less-developed world are driving wealthy countries toward a global reckoning with the fossil-fuel-powered, high-consumption, industrial way of life.

… The Tyndall Centre for Climate Change Research in the United Kingdom has estimated that some 23% of China’s total emissions result from net exports to the developed world. The Earth’s atmosphere bears a message: we are all in this together. China and climate change have collapsed us and them into we.”

“As someone very concerned about climate I want to be as aggressive as possible but I also want to get started. And if we say we want something much more aggressive on the early timescales that would draw considerable opposition and that would delay the process for several years. … But if I am going to say we need to do much, much better I am afraid the US won’t get started.”

However, Chu went on to discuss his aims for a “massive programme of efficiency for commercial buildings”, vastly improved cost-effectiveness of solar energy, and an interconnected wind power grid. The Obama climate change bill is making progress, but the slow movement on energy policy because of domestic resistance to change has potential global consequences. If the economically more developed countries of the world cannot show that their populations are willing and able to change their lifestyles to be less consumptive, negotiations with developing countries will be hindered.

Pressure from lower levels of government will help push things along. Last week 178 Michigan scientists (including myself) signed a letter to the Michigan Congressional delegation calling for actions to achieve strong and effective federal climate change solutions policies. And scientists can (and need) to do more than just write letters and do their basic (physical) research in their laboratories and at their computers. Reiterating his commitment to science in an address to the National Academy of Science, President Obama asked scientists and academics to engage in society to inspire and enable people “to be makers of things, not just consumers of things”.

A paper by David Pimentel and colleagues, entitled Energy efficiency and conservation for individual Americans, provides some solid numbers and ideas about how we as individual citizens in the economically more developed world can modify our residential energy use, reduce the impact of personal transport, and make informed decisions about what we eat. I’ve listed some of their more interesting suggestions for a sustainable lifestyle below. These are rational and effective ways we can change our lifestyles to live more sustainably and show that we are willing to share the responsibility of mitigating the human impact on the global environment. If we don’t want to be left with mere hope for a sustainable future, we need to show how others in the world can realise their hopes of development whilst conserving energy, water and our other natural resources.

Residential Energy Conservation

Improve and upgrade windows – 25% of residential heating and cooling energy is lost directly through single pane windows

Plant trees – deciduous on south to shade the house in the summer and allow full-sun in the winter, evergreen trees to the north can act as a wind-break

Use the microwave – it’s the most efficient way to steam, boil, and bake vegetables

Power-down your computer when it’s not in use – “computers should be turned off if the unit will be left for 2 hours or more and if left for 30 min the machine should be set in standby mode”

Pimentel and colleagues suggest that implementing these, and other, measures around the home would save around 5,600 kWh/year, resulting in savings of about $390/year on home energy costs.

Personal Transport

Drive slower – “A reduction in speed from 104 kmph (65 mph) to 86 kmph (55 mph) will reduce fuel consumption 19% (UrbanPlanet). For a 104 km trip, only an additional 11 min would be required if one traveled at 86 kmph. This extra 11 min would repay the person nearly $1.86 in fuel saving, or repay the person $10/h.”

Inflate your car tires properly – this will decrease the fuel consumption by up to 3%

Get rid of that junk in your trunk – “each 45 kg (100 pounds) of additional load in the car will reduce fuel mileage about 1%”

In summary: “[c]urrently, the average American uses about 1,900 l (500 gallons) of fuel/year in personal transport in contrast to the average person in the United Kingdom who consumes 1,700 l (450 gallons) (Renner 2003). If Americans implement the suggestions listed above [and others I haven’t listed] over a 10-year period, it would be possible to reduce fuel oil consumption between 10% and 20% from the current 20 quads of vehicle fuel [approximately 600 billion l or about 16 billion gallons of fuel] consumed in the U.S.”

Food systemThe authors highlight several ways in which farmers and policy-makers can aggressively pursue sustainable agricultural practices. They are less precise about what individuals’ can do but offer some general ideas:

Eat local products – reduces transport energy costs [and find out where you should buy your wine from here]

Eat less (especially less meat) – read more about meat and the environment here

“Select aluminum and steel packaging over glass or plastic, for energy conservation. For the same reasons, however, plastic and especially recyclable plastic should be selected instead of glass and/or paper.”

Pimentel et al. summarise: “[w]ell-directed, serious conservation strategies influenced by individuals with supportive state and federal leadership and policies will have an enormous positive impact on transitioning to a sustainable energy future for the United States.”

The second symposium I spent time in at US-IALE 2009, other than the CHANS workshop, was the Global Land Project Symposium on Agent-Based Modeling of Land Use Effects on Ecosystem Processes and Services. My notes for this symposium aren’t quite as extensive as for the CHANS workshop (and I had leave the discussion part-way through to give another presentation) but below I outline the main questions and issues raised and addressed by the symposium (drawing largely on Gary Polhill’s summary presentation).

The presentations highlighted the broad applicability of agent-based models (ABMs) across many places, landscapes and cultures using a diverse range of methodologies an populations. Locations and subjects of projects ranged from potential impacts of land use planning on the carbon balance in Michigan and rangeland management in the Greater Yellowstone Ecosystem, through impacts of land use change on wildfire regimes in Spain and water quality management in Australia, to conflicts between livestock and reforestation efforts in Thailand and the resilience of pastoral communities to drought Kenya. It was suggested that this diversity is a testament to the flexibility and power of the agent-based modelling approach. Methodologies used and explored by the projects in the symposium included:

In our discussion following the presentation it was interesting to have some social scientists join in the discussion that was dominated by computer scientists and modellers. Most interestingly was the viewpoint of a social scientist (a political scientist I believe) who suggested that one reason social scientists may be skeptical of the power of ABMs is that social science inherently understands that ‘some agents are more important than others’ and that this is not often well reflected (or at least analysed) in recent agent-based modelling.

Possibly the most important question raised in discussion was ‘what are we [as agent-based modellers] taking back to science more generally?’ There were plenty of examples in the projects about issues that have wider scientific applicability; scale issues, the intricacies of (very) large scale simulation with millions of agents, the integration of social and ecological complexity, forest transition theory, edge effects in models, and the presence of provenance (path-dependencies) in model dynamics. Agent-based modellers clearly deal with many interesting problems encountered and investigated in other areas of science, but whether we are doing a good job at communicating our experiences of these issues to the wider scientific community is certainly something open to debate (and was in the symposium).

A related question, recently raised on the SIMSOC listserv (but not in the GLP sumposium) is ‘what are ABMs taking back to policy-making and policy-makers’? Specifically, Scott Moss asked the question; ‘Does anyone know of a correct, real-time, [agent] model-based, policy-impact forecast? His reasoning behind this question is as follows:

“In relation to policy, it is common for social scientists (including but not exclusively economists) to use some a priori reasoning (frequently driven by a theory) to propose specific policies or to evaluate the benefits of alternative policies. In either case, the presumption must be that the benefits or relative benefits of the specified policies can be forecast. I am not aware of any successful tests of this presumption and none of my colleagues at the meeting of UK agent-based modelling experts could point me to a successful test in the sense of a well documented correct forecast of any policy benefit.

The importance of the question: If there is no history or, more weakly, no systematic history of successful forecasts of policy impacts, then is the standard approach to theory-driven policy advice defensible? If so, on what grounds? If not, then is an alternative approach to policy analysis and an alternative role for policy modelling indicated?”

The two most interesting replies were from Alan Penn and Mike Batty. Penn suggested [my links added]:

“… the best description I have heard of ‘policy’ in the sense you are using was by Peter Allen who described it “at best policy is a perturbation on the fitness landscape“. Making predictions of the outcome of any policy intervention therefore requires a detailed understanding of the shape of the mophogenetic landscape. Most often a perturbation will just nudge the system up a wall of the valley it is in, only for it to return back into the same valley and no significant lasting effect will be seen. On occasion a perturbation will nudge the trajectory over a pass into a neighbouring valley and some kind of change will result, but unless you have a proper understanding of the shape of this landscape you wont necessarily be able to say in advance what the new trajectory will be.

What this way of thinking about things implies is that what we need to understand is the shape of the fitness landscape. With that understanding we would be able to say how much of a nudge is needed (say the size of a tax incentive) to get over a pass. We would also know what direction the neighbouring ‘valleys’ might take the system, and this would allow predictions of the kind you want.”

Batty:

“I was at the meeting where Scott raised this issue. Alan Wilson said that his company GMAP was built on developing spatial interaction models for predicting short term shifts in retailing activity which routinely produced predictions that were close to the mark. There are no better examples than the large retail units that routinely – every week – run their models to make predictions in retail markets and reportedly they produce good predictions. These are outfits like Tesco, Asda, M[orrisons] and S[ainsbury’s] and so on. I cant give you chapter and verse of where these predictions have been verified and documented because I am an academic and dont have access to this sort of material. The kinds of models that I am referring to are essentially land use transport models which began in the 1960s and are still widely used today. Those people reading this post who arent familiar with these models because they are not agent based models can get a quick view by looking at my early book which is downloadable …

I think that the problem with this debate is that it is focussed on academia and academics don’t traditionally revisit their models to see if longer term predictions work out. In fact for the reasons Alan [Penn] says one would probably not expect them to work out as we cant know the future. However there is loads of evidence about how well some models such as the ones I have referred to can fit existing data – ie in terms of their calibration. My book and lots of other work with these models shows that can predict the baseline rather well. In fact too well and the problem has been that although they predict the baseline well, they can often be quite deficient at predicting short term change well and often this arises from their cross sectional static nature and a million other problems that have been raised over the last 30 or more years.”

In response to Batty, Moss wrote:

“It is by no means unusual for model-based forecasts to be sufficiently accurate that the error is less than the value of the variable and perhaps much less. What systematically does not happen (and I know of no counterexample at all) is correct forecasting of volatile episodes such as big shifts in market shares in retail sales, macroeconomic recessions or recoveries, the onset of bear or bull phases in financial markets.

Policy initiatives are usually intended to change something from what has gone on before. Democratic governments — executive and legislative branches — typically investigate the reasons for choosing one policy rather than another or, at least, justify a proposed policy before implementation. Sometimes these justifications are based on forecasts of impacts derived from models. Certainly this is happening now in relation to the current recession. So the question is not whether there are ever correct forecasts. Certainly on the minimal criteria I suggested, there are many. The question is strictly about forecasts of policy impacts which, I conjecture, are rather like other major shifts in social trend and stability.

I believe this particular question is important because I don’t understand the point of policy modelling if we cannot usefully inform policy formation. If the usefulness we claim is that we can evaluate policy impacts and, in point of fact, we systematically (or always) produce incorrect forecasts of the direction and/or timing of intended changes, then it seems hard to argue that this is a useful exercise.”

But is focussing on the accuracy of forecasts of the future the only, or indeed best, way of using models to inform policy? In recent times some policy-makers (e.g. Tony Blair and New Labour) have come to see science (and it’s tools of modelling and predictions) as some kind of a ‘policy saviour’, leading to what is known as evidence-based policy-making. In this framework, science sits upstream of policy-making providing evidence about the real state of the world that then trickles down to steer policy discourse. This may be fine when the science is solving puzzles, but there are many instances (climate change for instance) where science has not solved the problem and rather has merely demonstrated more clearly our ignorance and uncertainty about the material state of the world.

Science, generally, is about finding out about how the material world is. Policy, generally, is about deciding and making how the world how it ought to be. In many instances science can only provide an incomplete picture of how the world is, and even when it is confident about the material state of the world, there is only some much it can provide to an argument about how we think the world should be (which is what policy-making is all about). Emphasising the use of scientific models and modelling as a discussant, not a predictor, may be the best way to inform policy formulation.

In a paper submitted with one of my PhD advisors we discuss this sort of thing with reference to ‘participatory science’. The GLP ABM symposium is planning on publishing a special issue of Land Use Science containing papers from the meeting – in the manuscript I will submit I plan to follow-up in more detail on some of these participatory and ‘model as discussant’ issues with reference to my own agent-based modelling.

A while ago I heard this interview with Peter Orszag, Director of the US Office of Management and Budget and one of President Obama’s key economic advisors. Interestingly to me, given what I’ve written previously about quantitative models of human social and economic activity, Orszag is interested in Behavioural Economics and is somewhat skeptical about the power of mathematical models:

“Too many academic fields have tried to apply pure mathematical models to activities that involve human beings. And whenever that happens — whether it’s in economics or health care or medical science — whenever human beings are involved, an approach that is attracted by that purity will lead you astray”

That’s not to say he’s not going to use some form of model forecasting to do his job. When Jon Stewart highlights (in his own amusingly honest way) the wide range of economic model projections out there for the US deficit, Orszag points out that he needs at least some semblance of a platform from which to anchor his management of the US economy. But it’s reassuring for me to know that in managing the future this guy won’t be seduced by quantitative predictions of it.

Even if they aren’t quite what was discussed on Friday, it’s still interesting stuff. Nelson’s argument is that if the only reason we have to live sustainably is the hope that environmental disaster will be averted, it’s unlikely that we’ll actually avert those disasters. Why? Because hope is a pretty weak argument when confronted by a continual news stream about how unsustainable western societies are and because many messages suggest disaster is inevitable.

It seems much of this argument stems from Nelson’s dissatisfaction with books like Jared Diamond’s Collapse which spends the vast majority of 500 pages discussing the demise of previous societies and what could go wrong now, then finishing with a 5 page section entitled Reasons for Hope.

Cronon argued that global, ‘prophetic’ narratives are politically and socially inadequate because they don’t offer the possibility of individual or group action to address global problems. Such ‘big’ issues are hard for individuals to feel like they can do anything about.

Part of Cronon’s solution was the identification of ‘smaller’ (more focused) stories that individuals will be better able to empathise with. However, Cronon also played the hope card – suggesting that these more focused narratives offer individuals more hope than the global narratives.

Focusing on smaller issues closer to home may help – doesn’t hope become a stronger argument when the problems faced are less complex and the solutions are seemingly closer at hand? But Nelson seems to be suggesting that (as any ardent sports fan will tell you) it’s the hope that kills you.

“Instead of hope we need to provide young people with reasons to live sustainably that are rational and effective. We need to equate sustainable living, not so much with hope for a better future, but with basic virtues such as sharing and caring, which we already recognize as good in and of themselves, and not because of their measured consequences.”

Nelson’s is an ethical argument – that living sustainably should be portrayed as the ‘the right thing to do’, and that we should do it regardless of the consequences.

But then the question arises: how do we live sustainably? How do I know what the right thing to do is? Given a choice (on what printer paper to buy, for example) what decision to I make if I want to be sustainable? In order to make this choice we immediately need to start measuring the future consequences of our decisions. The future is an inherent part of the sustainability concept – it is about maintaining system processes or function into the future. So when we make our lifestyle decisions now, guided as they might be by the virtue of ‘doing the right thing’, we still need to have some idea about how we want the future to be, and which actions are more likely to get us there.

Nelson may be right – blind hope in a better future may prove counter productive given the current stream of global, prophetic, doomsaying narratives. But equally, just saying ‘do the right thing’ may be equally confusing for many people. Nelson isn’t arguing that this is all we should do, of course – he also suggests there is a “desperate need for environmental educators, writers, journalists and other leaders to work these [virtuous] ideas into their efforts”. It would be a good thing if living sustainably was more widely understood as ‘doing the right thing’. But this virtue will remain largely irrelevant if we don’t also work out how individuals and societies can live sustainably.

So what’s the result of all this thinking? It seems we should be focusing less on on doomsaying prophetic narratives (boiling seas bleaching coral reefs on continents thousands of miles away, stories of global warming when there’s a foot of snow outside, and so on) and more on what the individual person or group can do now, themselves, practically. In conjunction with the argument of acting virtuously with respect to sustainability, this focus may provide people with ‘rational and effective’ reasons, leaving them feeling more optimistic about the future and empowered to lead sustainable lives.

Update – 6th MarchOkay, how about a couple of quick examples to go with that rhetoric? The cover story of this month’s National Geographic Magazine is a good one – Peter Miller looks at how we can start making energy savings (reducing CO2 emissions) around our own homes. And of course, I should have already pointed out the BBC’s Ethical Man as he works out how to keep his environmental impact to a minimum. Currently he’s attemting to traverse the USA without flying or driving. The ethics of Ethical Man are more implied than stated explicitly, but it’s another example of the sort of reporting is discussed above – showing how individuals can act now rather than merely hoping for a better future.

Towards the end of last week the MSU Environmental Science and Public Policy Program held a networking event on Coupled Human and Natural Systems (CHANS). These monthly events provide opportunities for networking around different environmental issues and last week was the turn of the area CSIS focuses on. The meeting reminded me of a couple of things I thought I would point out here.

First is the continued commitment that the National Science Foundation (NSF) is making to funding CHANS research. The third week in November will be the annual deadline for research proposals, so watch out for (particularly) tired looking professors around that time of year.

Second, I realized I haven’t highlighted on this blog one of the NSF CHANS projects currently underway at CSIS. CHANS-Net aims to develop an international network of research on CHANS to facilitate communication and collaboration among members of the CHANS research community. Central to the project is the establishment of an online meeting place for research collaboration. An early version of the website is currently in place but improvements are in the planning. I was asked for a few suggestions earlier this week and it made me realise how interested I am in the potential of the technologies that have arrived with web 2.0 (I suppose that interest is also clear right here in front of you on this blog). I hope to be able to continue to make suggestions and participate in the development of the site from afar (there’s too much to be doing elsewhere to get my hands really dirty on that project). Currently, only Principle Investigators (PIs) and Co-PIs on NSF funded CHANS projects are members of the network, but hopefully opportunities for wider participation will be available in the future. In that event, I’ll post again here.

In particular, I suggested that if prediction of a future system state is our goal we will be best served focusing our modelling efforts on the natural system and then using that model with scenarios of future human behaviour to examine the plausible range of states the natural system might take. Alternatively, if we view modelling as an exclusively heuristic tool we might better envisage the modeling process as a means to facilitate communication between disparate groups of experts or publics and explore what different conceptualisations allow and prevent from happening with regards our stewardship or management of the system. Importantly, in both cases the act of making our implicitly held models of how the world works explicit by laying down a formal model structure is the primary value of modelling CHANS.

There was brief talk towards the end of the meeting about setting up a workshop website that might even contain audio/video recordings of presentations and discussions that took place. If such a website appears I’ll link to it here. In the meantime, the next meeting I’ll be attending on campus is likely to be the overview of Coupled Human-Natural Systems discussion in the Networking for Environmental Researchers program.

Previously, I wrote about Orrin Pilkey and Linda Pilkey-Jarvis’ book, Useless Arithmetic: Why Environmental Scientists Can’t Predict the Future. In a recent issue of the journal Futures, Jerome Ravetz reviews their book alongside David Waltner-Toews’ The Chickens Fight Back: Pandemic Panics and Deadly Diseases That Jump From Animals to Humans. Ravetz himself points out that the subject matter and approaches of the books are rather different, but suggests that “Read together, they provide insights about what needs to be done for the creation of a genuine science of sustainability”.

Ravetz (along with Silvio Funtowicz) has developed the idea of ‘post-normal’ science – a new approach to replace the reductionist, analytic worldview of ‘normal’ science. Post-normal science is a “systemic, synthetic and humanistic” approach, useful in cases where “facts are uncertain, values in dispute, stakes high and decisions urgent”. I used some of these ideas to experiment with some alternative model assessment criteria for the socio-ecological simulation model I developed during my PhD studies. Ravetz’s perspectives toward modelling, and science in general, shone through quite clearly in his review:

“On the philosophical side, the corruption of computer models can be understood as the consequence of a false metaphysics. Following on from the prophetic teachings of Galileo and Descartes, we have been taught to believe that Science is the sole and certain path to truth. And this Science is mathematical, using quantitative data and abstract reasonings. Such a science is not merely necessary for achieving genuine knowledge (an arguable position) but is also sufficient. We are all victims of the fantasy that once we have numerical data and mathematical argument (or computer programs), truth will inevitably follow. The evil consequences of this philosophy are quite familiar in neo-classical economics where partly true banalities about markets are dressed up in the language of the differential calculus to produce justifications for every sort of expropriation of the weak and vulnerable. ‘What you can’t count, doesn’t count’ sums it all up neatly. In the present case, the rule of models extends over nearly all the policy-relevant sciences, including those ostensibly devoted to the protection of the health of people and the environment.

We badly need an effective critical philosophy of mathematical science. … Now science has replaced religion as the foundation of our established order, and in it mathematical science reigns supreme. Systematic philosophical criticism is hard to find. (The late Imre Lakatos did pioneering work in the criticism of the dogmatism of ‘modern’ abstract mathematics but did not focus on the obscurities at the foundations of mathematical thinking.) Up to now, mathematical freethinking is mainly confined to the craftsmen, with their jokes of the ‘Murphy’s Law’ sort, best expressed in the acronym GIGO (Garbage In, Garbage Out). And where criticism is absent, corruption of all sorts, both deliberate and unaware, is bound to follow. Pseudo-mathematical reasonings about the unthinkable helped to bring us to the brink of nuclear annihilation a half-century ago. The GIGO sciences of computer models may well distract us now from a sane approach to coping with the many environmental problems we now face. The Pilkeys have done us a great service in providing cogent examples of the situation, and indicating some practical ways forward.”

Thus, Ravetz finds a little more value in the Useless Arithmetic book than I did. But equally, he highlights that the Pilkeys offer few, rather vague, solutions and instead turns to Waltner-Toews’ book for inspiration for the future:

Pilkey’s analysis of the corruptions of misconceived reductionist science shows us the depth of the problem. Waltner-Toews’ narrative about ourselves in our natural context (not always benign!) indicates the way to a solution.”

Using the outbreak of avian flu as an example of how to tackle complex environmental in the ‘risk society’ in which we now live, Waltner-Toews:

“… makes it very plain that we will never ‘conquer’ disease. Considering just a single sort of disease, the ‘zoonoses’ (deriving from animals), he becomes a raconteur of bio-social-cultural medicine …

What everyone learned, or should have learned, from the avian flu episode is that disease is a very complex entity. Judging from TV adverts for antiseptics, we still believe that the natural state of things is to be germ-free, and all we need to do is to find the germs and kill them. In certain limiting cases, this is a useful approximation to the truth, as in the case of infections of hospitals. But even there complexity intrudes … “

Complexity which demands an alternative perspective that moves beyond the next stage of ‘normal’ science to a post-normal science (to play on Kuhn’s vocabulary of paradigm shifts):

“That old simple ‘kill the germ’ theory may now be derided by medical authorities as something for the uneducated public and their media. But the practice of environmental medicine has not caught up with these new insights.

The complexity of zoonoses reflects the character of our interaction with all those myriads of other species. … the creatures putting us at risk are not always large enough to be fenced off and kept at a safe distance. … We can do all sorts of things to control our interactions with them, but one thing is impossible: to stamp them out, or even to kill the bad ones and keep the good ones.

Waltner-Toews is quite clear about the message, and about the sort of science that will be required, not merely for coexisting with zoonoses but also for sustainable living in general. Playing the philological game, he reminds us that the ancient Indo-European world for earth, dgghem, gave us, along with ‘humus’, all of ‘human’, ‘humane’ and ‘humble’. As he says, community by community, there is a new global vision emerging whose beauty and complexity and mystery we can now explore thanks to all our scientific tools.”

This global vision is a post-normal vision. It applies to far more than just avian flu – from coastal erosion and the disposal of toxic or radioactive waste (as the Pilekys discuss for example) to climate change. This post-normal vision focuses on uncertainty, value loading, and a plurality of legitimate perspectives that demands an “extended peer community” to evaluate the knowledge generated and decisions proposed.

In all fairness, it would not be easy to devise a conventional science-based curriculum in which Waltner-Toews’ insights could be effectively conveyed. For his vision of zoonoses is one of complexity, intimacy and contingency. To grasp it, one needs to have imagination, breadth of vision and humility, not qualities fostered in standard academic training. … “

This post-normal science won’t be easy and won’t be learned or fostered entirely within the esoteric confines of an ivory tower. Science, with its logical rigour, is important. It is still the best game in town. But the knowledge produced by ‘normal’ science is provisional and its march toward truth is seemingly Sisyphean when confronted faced with the immediacy of complex contemporary environmental problems. To contribute to the production a sustainable future, a genuine science of sustainability would do well to adopt a more post-normal stance toward its subject.